The need for the invention was first raised in a Juvenile Justice setting. Juvenile courts, unlike their adult counterparts, focus on rehabilitation of the offender (vs. punishment). As a result, these agencies need to provide programs, services, and interventions that address the assessment and rehabilitation of these young offenders. Some programs are offered directly by the court (e.g. probation services), but most are provided by outside agencies.
The goal is for offenders to be assessed and then referred to programs that hold promise of impacting the youth in a positive way. It is important that the referrals direct the youth to appropriate programs for his/her needs (and risk). Assessments are conducted to determine the characteristics of the subject (e.g. demographic information such as sex, race, age, socioeconomic situation, but also behavioral, physical, psychiatric needs, risks, strengths, weakness, etc.). The candidate programs, on the other hand, have characteristics (i.e. mission, goals, expertise, target audience, capability, capacity, cost, eligibility requirements, etc.) In an ideal world, some exceptionally skilled and informed case worker or court official would match the youth, having documented characteristics, to the best program(s), having documented characteristics. Making this “matching” decision would also take into account the information “what intervention works best for what kind of youth? And are these intervention services offered by the available programs?” These are among the criteria used to measure how “good” a candidate match might promise to be.
Answering these questions is a very complex and data intensive task, especially with thousands of youth and scores of different programs from which to choose. Methods of assessing and characterizing the youth and programs, documenting the level of participation and the interventions used, and capturing the outcomes of historical matches are needed. And, importantly, information technology in the form of data-collection, database and analysis tools are needed to enable the methodology.
Static information about the youth as well as longitudinal and dynamic information about the youth's needs, behaviors, attitudes, etc., together with longitudinal intervention information related to his/her participation in multiple programs, program service-delivery information and goals, must be captured. Furthermore, this information needs to be captured in a format that can accommodate very different kinds of data coming from many different sources. The data-collection method and tool need to be flexible yet robust.
The problem of maintaining youth assessment information alone is a daunting task. Assessment instruments (e.g. questionnaires, survey forms, etc.) vary from program to program. And often there are multiple assessment instruments used within the same program. Frequently, questions are shared by multiple instruments. Similar questions are expressed inconsistently across instruments (e.g. one expression of the question might be in a multiple-choice format, while another might be free format.) The assessment instrument itself is often dynamic, having questions added, changed, or deleted over time. The sheer number of instruments and information elements is overwhelming, and maintaining such instruments within an information system could require major and ongoing programming effort to “program them into and then maintain them” within the application.
There is a growing universal and pressing need for methods and tools to assist in program outcome measurement, and, more generally, to program evaluation. This impetus has arisen partially due to the presence of more and more human service programs and the rise in non-profit initiatives. Also, funders of such programs are demanding accountability and are expecting to see how their contributions are being used. United Way has recently mandated that its member agencies implement Program Outcomes Measurement programs and methods, and is actively training these agencies in this practice.